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Tired of AI coding assistants that spit out generic code?
Anthropic's CEO gives great insight into the DeepSeek models, cost curves, and innovation. He expertly lays out the landscape and points to flaws in the market reaction. Additionally, he reveals that Sonnet 3.5 only cost $10m or so dollars to train. The main point of the article is export controls.
OpenAI has found evidence that the Chinese AI startup DeepSeek used its proprietary models to train an open-source competitor. The suspected "distillation" process allows smaller models to mimic larger ones at a lower cost, raising concerns over intellectual property breaches.
Mark Zuckerberg remains unfazed by competition from DeepSeek. He has reaffirmed Meta's commitment to massive AI investments and focus on model development and computational resources.
The Qwen team has released its MoE earlier than expected. The model shows really strong performance, matching many top models, including DeepSeek v3.
One of the key levers that can be pulled to reduce training and inference costs is quantization. Getting these models to run at lower precision saves on the number of GPUs and FLOPs needed for training. This work shows, on a small scale of 100B tokens, how to train at FP4.
CascadeV introduces a cascaded latent diffusion model that generates 2K-resolution videos with improved efficiency. It employs a novel 3D attention mechanism and can be integrated with existing text-to-video models to enhance resolution and frame rate without fine-tuning.
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With new models popping up every day, you want to stay flexible. You.com [13] gives you the freedom to switch between models on the fly, including the latest models from OpenAI, DeepSeek, and Anthropic.
Mamba-Shedder is a method that optimizes structured state space models by selectively removing redundant components. The approach improves inference speed by up to 1.4x while maintaining model accuracy.
This project introduces Generative Psychometrics for Values, a novel method that uses large language models to measure human and AI values.
TART enhances large language models by integrating them with computational tools, improving accuracy and transparency in tasks like finance, science, and healthcare.
Microsoft and USC conducted a study using GPT-4 to explore how generative AI affects writers' authenticity and creativity. Writers expressed concerns about AI impacting originality, emotional satisfaction, and ownership of work. Despite initial skepticism, personalized AI models that align with a writer's style helped alleviate these concerns, enhancing creativity without compromising authenticity.
Interview Mega HR has launched "Megan", an AI agent designed to streamline and automate recruitment processes. Megan handles tasks from job posting to candidate management, aiming to improve hiring efficiency and transparency.
Nathan Lambert breaks down the recipe for R1 and talks through what it means for us now and for the field broadly. Specifically, he focuses on the interesting application of reinforcement learning.
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Google used LLMs to significantly speed up internal code migrations, such as transitioning Google Ads' 32-bit to 64-bit IDs.
Google has introduced the Titans architecture, an evolution of Transformers that incorporates neural long-term memory for better data retention and "surprise-based" learning.
OpenAI, Anthropic, and Meta are partnering with U.S. military agencies to use AI for threat identification and planning.